Due Jan 26, 2024 @ 11:59PM (New deadline Feb 5th Extension due to Mac Repairs)
Author
Kathy Hoang, UID: 506333118
Display machine information for reproducibility:
sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.2
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/Los_Angeles
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] htmlwidgets_1.6.4 compiler_4.3.2 fastmap_1.1.1 cli_3.6.2
[5] tools_4.3.2 htmltools_0.5.7 rstudioapi_0.15.0 yaml_2.3.8
[9] rmarkdown_2.25 knitr_1.45 jsonlite_1.8.8 xfun_0.41
[13] digest_0.6.34 rlang_1.1.3 evaluate_0.23
Q1. Git/GitHub
No handwritten homework reports are accepted for this course. We work with Git and GitHub. Efficient and abundant use of Git, e.g., frequent and well-documented commits, is an important criterion for grading your homework.
Apply for the Student Developer Pack at GitHub using your UCLA email. You’ll get GitHub Pro account for free (unlimited public and private repositories).
Create a private repository biostat-203b-2024-winter and add Hua-Zhou and TA team (Tomoki-Okuno for Lec 1; jonathanhori and jasenzhang1 for Lec 80) as your collaborators with write permission.
Top directories of the repository should be hw1, hw2, … Maintain two branches main and develop. The develop branch will be your main playground, the place where you develop solution (code) to homework problems and write up report. The main branch will be your presentation area. Submit your homework files (Quarto file qmd, html file converted by Quarto, all code and extra data sets to reproduce results) in the main branch.
After each homework due date, course reader and instructor will check out your main branch for grading. Tag each of your homework submissions with tag names hw1, hw2, … Tagging time will be used as your submission time. That means if you tag your hw1 submission after deadline, penalty points will be deducted for late submission.
After this course, you can make this repository public and use it to demonstrate your skill sets on job market.
This exercise (and later in this course) uses the MIMIC-IV data v2.2, a freely accessible critical care database developed by the MIT Lab for Computational Physiology. Follow the instructions at https://mimic.mit.edu/docs/gettingstarted/ to (1) complete the CITI Data or Specimens Only Research course and (2) obtain the PhysioNet credential for using the MIMIC-IV data. Display the verification links to your completion report and completion certificate here. You must complete Q2 before working on the remaining questions. (Hint: The CITI training takes a few hours and the PhysioNet credentialing takes a couple days; do not leave it to the last minute.)
I obtained the PhysioNet credential for using the MIMIC-IV data:
PhysioNetCredential.png
Q3. Linux Shell Commands
Make the MIMIC v2.2 data available at location ~/mimic.
Answer I created a symbolic link in my home directory called mimic pointing to the MIMIC v2.2 data folder.
ls-l ~/mimic/
total 48
-rw-rw-r--@ 1 kathyhoang staff 13332 Jan 5 2023 CHANGELOG.txt
-rw-rw-r--@ 1 kathyhoang staff 2518 Jan 5 2023 LICENSE.txt
-rw-rw-r--@ 1 kathyhoang staff 2884 Jan 6 2023 SHA256SUMS.txt
drwxr-xr-x@ 28 kathyhoang staff 896 Jan 31 01:35 hosp
drwxr-xr-x@ 11 kathyhoang staff 352 Jan 29 22:23 icu
Refer to the documentation https://physionet.org/content/mimiciv/2.2/ for details of data files. Please, do not put these data files into Git; they are big. Do not copy them into your directory. Do not decompress the gz data files. These create unnecessary big files and are not big-data-friendly practices. Read from the data folder ~/mimic directly in following exercises.
Use Bash commands to answer following questions.
Display the contents in the folders hosp and icu using Bash command ls -l. Why are these data files distributed as .csv.gz files instead of .csv (comma separated values) files? Read the page https://mimic.mit.edu/docs/iv/ to understand what’s in each folder.
ls-l ~/mimic/hosp
total 35858952
-rw-rw-r--@ 1 kathyhoang staff 73099499 Jan 30 16:33 admissions.csv
-rw-rw-r--@ 1 kathyhoang staff 15516088 Jan 5 2023 admissions.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 427468 Jan 5 2023 d_hcpcs.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 859438 Jan 5 2023 d_icd_diagnoses.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 578517 Jan 5 2023 d_icd_procedures.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 12900 Jan 5 2023 d_labitems.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 25070720 Jan 5 2023 diagnoses_icd.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 7426955 Jan 5 2023 drgcodes.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 508524623 Jan 5 2023 emar.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 471096030 Jan 5 2023 emar_detail.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 1767138 Jan 5 2023 hcpcsevents.csv.gz
-rw-r--r--@ 1 kathyhoang staff 13730083993 Feb 1 01:28 labevents.csv
-rw-rw-r--@ 1 kathyhoang staff 1939088924 Jan 5 2023 labevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 96698496 Jan 5 2023 microbiologyevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 36124944 Jan 5 2023 omr.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 9881607 Jan 30 17:39 patients.csv
-rw-rw-r--@ 1 kathyhoang staff 2312631 Jan 5 2023 patients.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 398753125 Jan 5 2023 pharmacy.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 498505135 Jan 5 2023 poe.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 25477219 Jan 5 2023 poe_detail.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 458817415 Jan 5 2023 prescriptions.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 6027067 Jan 5 2023 procedures_icd.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 122507 Jan 5 2023 provider.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 6781247 Jan 5 2023 services.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 36158338 Jan 5 2023 transfers.csv.gz
ls-l ~/mimic/icu
total 6155968
-rw-rw-r--@ 1 kathyhoang staff 35893 Jan 5 2023 caregiver.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 2467761053 Jan 5 2023 chartevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 57476 Jan 5 2023 d_items.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 45721062 Jan 5 2023 datetimeevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 2614571 Jan 5 2023 icustays.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 251962313 Jan 5 2023 ingredientevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 324218488 Jan 5 2023 inputevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 38747895 Jan 5 2023 outputevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 20717852 Jan 5 2023 procedureevents.csv.gz
Answer Gzip is a data compression program and .gz refers to the file format that results from using gzip compression. Thus, the data files are distributed as .csv.gz files instead of .csv files because they are compressed files. This compression technology reduces the size of the files and allows data to be transferred more quickly.
Briefly describe what Bash commands zcat, zless, zmore, and zgrep do.
Answer
#man zcat#man zless#man zmore#man zgrep#note: commented out to avoid long outputs
zcat: allows you to view the contents of a compressed (gzipped) file without having to decompress it. It is similar to the cat command, but it works on zipped files, hence the term zcat.
zless: is a command allows you to view the contents of a compressed file one screen at a time without having to decompress it. The biggest difference between the zless command and the zmore command is that zless offers more functionality and is a bit faster since it does not load the entire file into memory before it displays the output (less is more). It is similar to the less command, but it works on zipped files, hence the term zless.
zmore: is a command that allows you to view the contents of a compressed file one screen at a time without having to decompress it. It is similar to the more command, but it works on zipped files, hence the term zmore.
zgrep: is a command that allows you to search compressed files for a regular expression (matching patterns) without having to decompress it. It invokes the grep command, which is short for “global regular expression print”, on compressed/gzipped files.
(Looping in Bash) What’s the output of the following bash script?
for datafile in ~/mimic/hosp/{a,l,pa}*.gzdols-l$datafiledone
AnswerThe bash script loops through all the files in the hosp folder to find files that begin with a, l, or pa and end with .gz. The output is the resulting list of three files in the hosp folder that met the specified criteria: admissions.csv.gz, labevents.csv.gz, and patients.csv.gz.
Display the number of lines in each data file using a similar loop. (Hint: combine linux commands zcat < and wc -l.)
Answer
for datafile in ~/mimic/hosp/{a,l,pa}*.gzdozcat<$datafile|wc-ldone
431232
118171368
299713
Display the first few lines of admissions.csv.gz. How many rows are in this data file? How many unique patients (identified by subject_id) are in this data file? Do they match the number of patients listed in the patients.csv.gz file? (Hint: combine Linux commands zcat <, head/tail, awk, sort, uniq, wc, and so on.)
Answer
#Display the first 5 lines of admissions.csv.gzfor files in ~/mimic/hosp/admissions.csv.gzdozmore<$files|head-n 5done
#Number of rows in admissions.csv.gznum_rows=$(zless< ~/mimic/hosp/admissions.csv.gz |wc-l)echo There are $num_rows rows in admissions.csv.gz.
There are 431232 rows in admissions.csv.gz.
#Unique Patients in admissions.csv.gznum_uniq_pat=$(zless< ~/mimic/hosp/admissions.csv.gz |tail-n +2 |awk-F,'{print $1}'|sort|uniq|wc-l)echo There are $num_uniq_pat unique patients in admissions.csv.gz.#Scratchwork#Check that the column selected is subject_id#zcat < ~/mimic/hosp/admissions.csv.gz | awk -F, '{print $1}' | head#subject_id is the first column so print $1#tail -n +2 skips the first row, which is the header/column names so we don't want to include this in our count## + means line numbering should start from here#zless < ~/mimic/hosp/admissions.csv.gz | tail -n +2 | head -n 5
There are 180733 unique patients in admissions.csv.gz.
#Unique Patients in patients.csv.gznum_pat=$(zcat< ~/mimic/hosp/patients.csv.gz |tail-n +2 |awk-F,'{print $1}'|sort|uniq|wc-l)echo There are $num_pat unique patients in patients.csv.gz.#Scratchwork#Print first few lines of patients.csv.gz using head#zcat < ~/mimic/hosp/patients.csv.gz | head#subject_id is the first column so print $1
There are 299712 unique patients in patients.csv.gz.
The number of unique patients in the admissions.csv.gz file, 180733, does not match the number of patients listed in the patients.csv.gz file, 299712. This is because the patients listed in the admissions.csv.gz file represent only the patients who have been admitted to the hospital, while the patients listed in the patients.csv.gz file represent all of the patients in the database.
What are the possible values taken by each of the variable admission_type, admission_location, insurance, and ethnicity? Also report the count for each unique value of these variables. (Hint: combine Linux commands zcat, head/tail, awk, uniq -c, wc, and so on; skip the header line.)
Answer Admission Type is of data type: VARCHAR(40) NOT NULL and there are 9 possible values:‘AMBULATORY OBSERVATION’, ‘DIRECT EMER.’, ‘DIRECT OBSERVATION’, ‘ELECTIVE’, ‘EU OBSERVATION’, ‘EW EMER.’, ‘OBSERVATION ADMIT’, ‘SURGICAL SAME DAY ADMISSION’, and ‘URGENT’. These are the counts for each unique value:
#zless < ~/mimic/hosp/admissions.csv.gz | head -n 5#column numbers: 6 (admission_type), 8 (admission_location), 10(insurance), 13(race)#Note: uniq -c counts the number of occurrences of each unique value#Admission Typezless< ~/mimic/hosp/admissions.csv.gz |tail-n +2 |awk-F,'{print $6}'|sort|uniq-c
6626 AMBULATORY OBSERVATION
19554 DIRECT EMER.
18707 DIRECT OBSERVATION
10565 ELECTIVE
94776 EU OBSERVATION
149413 EW EMER.
52668 OBSERVATION ADMIT
34231 SURGICAL SAME DAY ADMISSION
44691 URGENT
Admission Location is of data type VARCHAR(60) and there are 11 possible values: ‘AMBULATORY SURGERY TRANSFER’, ‘CLINIC REFERRAL’, ‘EMERGENCY ROOM’, ‘INFORMATION NOT AVAILABLE’, ‘INTERNAL TRANSFER TO OR FROM PSYCH’, ‘PACU’, ‘PHYSICIAN REFERRAL’, ‘PROCEDURE SITE’, ‘TRANSFER FROM HOSPITAL’, ‘TRANSFER FROM SKILLED NURSING FACILITY’, and ‘WALK-IN/SELF REFERRAL’. These are the counts for each unique value:
185 AMBULATORY SURGERY TRANSFER
10008 CLINIC REFERRAL
232595 EMERGENCY ROOM
359 INFORMATION NOT AVAILABLE
4205 INTERNAL TRANSFER TO OR FROM PSYCH
5479 PACU
114963 PHYSICIAN REFERRAL
7804 PROCEDURE SITE
35974 TRANSFER FROM HOSPITAL
3843 TRANSFER FROM SKILLED NURSING FACILITY
15816 WALK-IN/SELF REFERRAL
Insurance is of data type VARCHAR(255) and there are 3 possible values: ‘Medicaid’, ‘Medicare’, and ‘Other’. These are the counts for each unique value:
919 AMERICAN INDIAN/ALASKA NATIVE
6156 ASIAN
1198 ASIAN - ASIAN INDIAN
5587 ASIAN - CHINESE
506 ASIAN - KOREAN
1446 ASIAN - SOUTH EAST ASIAN
2530 BLACK/AFRICAN
59959 BLACK/AFRICAN AMERICAN
4765 BLACK/CAPE VERDEAN
2704 BLACK/CARIBBEAN ISLAND
7754 HISPANIC OR LATINO
437 HISPANIC/LATINO - CENTRAL AMERICAN
639 HISPANIC/LATINO - COLUMBIAN
500 HISPANIC/LATINO - CUBAN
4383 HISPANIC/LATINO - DOMINICAN
1330 HISPANIC/LATINO - GUATEMALAN
536 HISPANIC/LATINO - HONDURAN
665 HISPANIC/LATINO - MEXICAN
8076 HISPANIC/LATINO - PUERTO RICAN
892 HISPANIC/LATINO - SALVADORAN
560 MULTIPLE RACE/ETHNICITY
386 NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER
15102 OTHER
1761 PATIENT DECLINED TO ANSWER
1510 PORTUGUESE
505 SOUTH AMERICAN
1603 UNABLE TO OBTAIN
10668 UNKNOWN
272932 WHITE
1103 WHITE - BRAZILIAN
1170 WHITE - EASTERN EUROPEAN
7925 WHITE - OTHER EUROPEAN
5024 WHITE - RUSSIAN
To compress, or not to compress. That’s the question. Let’s focus on the big data file labevents.csv.gz. Compare compressed gz file size to the uncompressed file size. Compare the run times of zcat < ~/mimic/labevents.csv.gz | wc -l versus wc -l labevents.csv. Discuss the trade off between storage and speed for big data files. (Hint: gzip -dk < FILENAME.gz > ./FILENAME. Remember to delete the large labevents.csv file after the exercise.)
Answer
#Size of gz filels-l ~/mimic/hosp/labevents.csv.gz#1939088924 bytesls-lh ~/mimic/hosp/labevents.csv.gz#1.8 GB#Size of uncompressed file gzip-dk< ~/mimic/hosp/labevents.csv.gz > ~/mimic/hosp/labevents.csvls-l ~/mimic/hosp/labevents.csv#13730083993 bytesls-lh ~/mimic/hosp/labevents.csv#13 GB#Note: delete after exercise: ~/mimic/hosp/labevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 1939088924 Jan 5 2023 /Users/kathyhoang/mimic/hosp/labevents.csv.gz
-rw-rw-r--@ 1 kathyhoang staff 1.8G Jan 5 2023 /Users/kathyhoang/mimic/hosp/labevents.csv.gz
-rw-r--r--@ 1 kathyhoang staff 13730083993 Feb 1 02:02 /Users/kathyhoang/mimic/hosp/labevents.csv
-rw-r--r--@ 1 kathyhoang staff 13G Feb 1 02:02 /Users/kathyhoang/mimic/hosp/labevents.csv
#run time for compressedtime zcat < ~/mimic/hosp/labevents.csv.gz |wc-l#run time for uncompressedtime wc -l ~/mimic/hosp/labevents.csv
118171368
real 0m14.010s
user 0m21.879s
sys 0m1.248s
118171368 /Users/kathyhoang/mimic/hosp/labevents.csv
real 0m14.512s
user 0m12.999s
sys 0m1.180s
The uncompressed files are significantly larger than the compressed files. The uncompressed file labevents.csv is 1373008399 3bytes which is about 13 GB, in contrast to the compressed file ‘labevents.csv.gz’ is only 1939088924 bytes which is about 1.8GB.
The runtime output shows that ‘zcat < ~/mimic/labevents.csv.gz | wc -l’ took slightly longer than ‘wc -l ~/mimic/labevents.csv’. The difference in run time was more noticeable for user and system time, but real time is relatively the same.
The tradeoff between storage and speed between these compressed and uncompressed large data files is that compressed files save a lot more storage space but require a longer processing time, but uncompressed files take up an excessive amount of storage but are faster to process. However, this difference in processing time is not that significant for data files of this size.
Q4. Who’s popular in Price and Prejudice
You and your friend just have finished reading Pride and Prejudice by Jane Austen. Among the four main characters in the book, Elizabeth, Jane, Lydia, and Darcy, your friend thinks that Darcy was the most mentioned. You, however, are certain it was Elizabeth. Obtain the full text of the novel from http://www.gutenberg.org/cache/epub/42671/pg42671.txt and save to your local folder.
Explain what wget -nc does. Do not put this text file pg42671.txt in Git. Complete the following loop to tabulate the number of times each of the four characters is mentioned using Linux commands.
Answerwget -nc retrieves files via HTTP or FTP. It allows you to download a file from the internet from the given URL. The -nc option stands for “no clobber”, and it is used to avoid overwriting existing files. If the file already exists, it will not be downloaded again if you run wget again.
wget-nc http://www.gutenberg.org/cache/epub/42671/pg42671.txtfor char in Elizabeth Jane Lydia Darcydoecho$char: $(grep-o-i$char pg42671.txt |wc-l)done#NOTES#loops through each character name#-o prints only matched characters instead of the whole line#-i ignores case#grep will search for pattern (char) in the file pg42671.txt#wc -l counts the number of lines and returns the number of times each of the 4 character is mentioned
What’s the difference between the following two commands?
echo'hello, world'> test1.txt#added my own commands to testecho'goodbye, world'> test1.txtcat test1.txt
and
echo'hello, world'>> test2.txt#added my own commands to testecho'goodbye, world'>> test2.txtcat test2.txt
Answer
One > OVERWRITES: The first command with only one > will create a new file with the given input, unless the file already exists, then it will overwrite the file with the given input. In this case, it first created a file with “hello, world” the first time it ran. However, when the second line was run, it rewrote “hello, world” with “goodbye, world”.
Two >> APPENDS: The second command with two >> will create a new file with the given input if it does not exist yet. If the file exists already, it will append the input to the end of the existing file. In the example above, it first created a file with “hello, world” the first time it ran. However, when the second line was run, it appended “goodbye, world” to “hello, world” so that the text file contained “hello, world” and “goodbye, world”.
Using your favorite text editor (e.g., vi), type the following and save the file as middle.sh:
#!/bin/sh# Select lines from the middle of a file.# Usage: bash middle.sh filename end_line num_lineshead-n"$2""$1"|tail-n"$3"
Answer I used the vi text editor. In the terminal, I typed “vi middle.sh” to create and start editing the file, pressed i to enter INSERT mode, and copied the code above. In order to save, I need to be in the COMMAND mode so I pressed ESC to exit the insert mode. Then I typed :wq to save and exit the file (:w saves and :q quits).
Using chmod to make the file executable by the owner, and run
chmod u+x middle.sh#make file execute to the user/owner./middle.sh pg42671.txt 20 5
Explain the output. Explain the meaning of "$1", "$2", and "$3" in this shell script. Why do we need the first line of the shell script?
Answer The initial argument, “$1”, is the filename, pg42671.txt. The second argument, “$2”, or end_line, represents the number of lines to be extracted from the file. The third argument, “$3”, is the number of lines to be extracted from the previous result.
Thus, the first line (head -n “$2” “$1”) will extract the lines from the beginning to the end_line (20) of the file given in the first argument (pg42671.txt). The second line of the shell script (tail -n “$3”) will then output the last 5 lines from the previous result of 20 lines. This will then return lines 16-20 of the file pg42671.txt. Both head and tail commands are required to extract the middle lines. Head allows you to specify the end (up to the last line you want), and tail will take a subset from the head output and allow you to specify the start (Tail will give you the last lines up to the start line you want).
[Note: unclear what you mean by first line of shell script so I’m including this too just in case] If you are referring to head -n “$2” “$1”, it was already explained above. If you are referring to #!/bin/sh, this is called a shebang, and it is used to specify the interpreter that the system should use to execute the script. In this case, it tells the system to use the Bourne shell (sh) to execute the script.
Q5. More fun with Linux
Try following commands in Bash and interpret the results: cal, cal 2024, cal 9 1752 (anything unusual?), date, hostname, arch, uname -a, uptime, who am i, who, w, id, last | head, echo {con,pre}{sent,fer}{s,ed}, time sleep 5, history | tail.
Answer Please refer to the comments in the code below for the interpretation of the results. The comments above correspond to the command below it.
#shows just this month's calendarcal#shows the calendar for the year 2024cal 2024#shows the calendar for specified month and year: September 1752cal 9 1752#September 1752 is unusual because it is missing dates Sept 3-13. #After doing further research, it turns out that the 11 days missing is #due to the delayed adoption of the Gregorian calendar by the British Empire #of the Gregorian calendar. These days were skipped as a result of#political and religious resistance to the calendar change #proposed by the Catholic Pope known as the "Calendar Riots of 1752".#Shows the current date and timedate#Shows the hostname of the machine (my computer) #Ex. CLICC-M-4739, my laptop is lent from UCLA's CLICC #but normally it would be my name kathyhoanghostname#Shows the architecture of the machine Ex.arm64arch# Shows detailed system information for the machine, including the kernel #version and the timestamp when the kernel was built, machine architecture#(arm64), and additional details about the kernel such as the #root and version information, etcuname-a#Shows the current time, how long the system has been running, #the number of users currently logged on, and the#system load averages for the past 1, 5, and 15 minutesuptime#Shows the current user and current timewho am i#Shows the current users logged in and when they logged inwho#Shows the current users logged in and information about the users' activitiesw#Shows user and group information, including the current user's UID and GIDid# Last displays previous logins and head limits it to the most recent 10 loginslast|head#This line creates a combination of words, uses the curly braces and comma to #make various permutations. The first set of curly braces contains prefix options, #the second set of curly braces contains the middle part of the word, and the #third set of curly braces contains the suffix options that will be appended to#the end. The comma separates the word options within the curly braces.echo{con,pre}{sent,fer}{s,ed}#Time measures the amount of time it takes to execute the sleep 5 command in#seconds. The sleep 5 command is used to pause the script for 5 seconds. #Thus, the output is about 5 seconds in real time, the user time is 0.001 seconds, #and the system time is 0.002 seconds.time sleep 5#Shows the last 10 commands that were executed in the terminalhistory|tail
Open the project by clicking rep-res-3rd-edition.Rproj and compile the book by clicking Build Book in the Build panel of RStudio. (Hint: I was able to build git_book and epub_book but not pdf_book.)
The point of this exercise is (1) to get the book for free and (2) to see an example how a complicated project such as a book can be organized in a reproducible way.
For grading purpose, include a screenshot of Section 4.1.5 of the book here.
AnswerI was able to build the book. Here is a screenshot of Section 4.1.5 of the book:
